Generative Models for Improved Naturalness, Intelligibility, and Voicing of Whispered Speech

Author:

Wagner Dominik1,Bayerl Sebastian P.1,Maruri Hector A. Cordourier2,Bocklet Tobias1

Affiliation:

1. Technische Hochschule Nürnberg Georg Simon Ohm,Germany

2. Intel Labs

Publisher

IEEE

Reference35 articles.

1. Learning to discover cross-domain relations with generative adversarial networks;kim;Proceedings of the 34th International Conference on Machine Learning,0

2. Autoencoding beyond pixels using a learned similarity metric;larsen;Proceedings of the 33rd International Conference on International Conference on Machine Learning,0

3. Effectiveness of Cross-Domain Architectures for Whisper-to-Normal Speech Conversion

4. Visualizing data using t-sne;van der maaten;Journal of Machine Learning Research,2008

5. Harmonics Plus Noise Model Based Vocoder for Statistical Parametric Speech Synthesis

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Streaming ASR Encoder for Whisper-to-Speech Online Voice Conversion;IEEE Open Journal of Signal Processing;2024

2. The Ethical Implications of Generative Audio Models: A Systematic Literature Review;Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society;2023-08-08

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